Publications by authors named "E W Kun"
Humans exhibit distinct characteristics compared to our primate and ancient hominin ancestors. To investigate genomic bursts in the evolution of these traits, we use two complementary approaches to examine enrichment among genome-wide association study loci spanning diseases and AI-based image-derived brain, heart, and skeletal tissue phenotypes with genomic regions reflecting four evolutionary divergence points. These regions cover epigenetic differences among humans and rhesus macaques, human accelerated regions (HARs), ancient selective sweeps, and Neanderthal-introgressed alleles.
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- * The study introduces enhanced modeling techniques for neutrino flux and detector response, and it distinguishes between starting (inside) and throughgoing (outside) neutrino interaction events to improve energy resolution.
- * The findings indicate a best-fit point for the 3+1 model with sin²(2θ_{24})=0.16 and Δm_{41}²=3.5 eV², supporting previous studies while showing consistency with no evidence of sterile neutrinos, as reflected
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- - The study presents a measurement of astrophysical tau neutrinos using 9.7 years of data from the IceCube observatory, identifying seven candidate events with energies between 20 TeV and 1 PeV.
- - Convolutional neural networks were used to analyze simulated event images, helping to estimate the parent tau neutrino energy to be around 200 TeV while facing a background of about 0.5 events primarily from non-tau astrophysical neutrinos.
- - The results confirmed the presence of astrophysical tau neutrinos at a 5σ significance level, aligning with existing IceCube measurements and theoretical predictions regarding neutrino flux and oscillations.
Electronic health records are often incomplete, reducing the power of genetic association studies. For some diseases, such as knee osteoarthritis where the routine course of diagnosis involves an X-ray, image-based phenotyping offers an alternate and unbiased way to ascertain disease cases. We investigated this by training a deep-learning model to ascertain knee osteoarthritis cases from knee DXA scans that achieved clinician-level performance.
View Article and Find Full Text PDFThe human skeletal form underlies bipedalism, but the genetic basis of skeletal proportions (SPs) is not well characterized. We applied deep-learning models to 31,221 x-rays from the UK Biobank to extract a comprehensive set of SPs, which were associated with 145 independent loci genome-wide. Structural equation modeling suggested that limb proportions exhibited strong genetic sharing but were independent of width and torso proportions.
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